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codingbuddy
codingbuddy contient 50 skills collectées depuis JeremyDev87, avec une couverture métier par dépôt et des pages de détail sur le site.
Skills dans ce dépôt
Use when orchestrating parallel Claude Code instances across tmux panes with git worktree isolation — managing multiple concurrent development tasks visually
Use when production incident occurs, alerts fire, service degradation detected, or on-call escalation needed - guides systematic organizational response before technical fixes
Use when conducting manual PR reviews - provides structured checklist covering security, performance, maintainability, and code quality dimensions with anti-sycophancy principles
Run local CI checks and ship changes — create branch, commit, push, and PR. Optionally link to a GitHub issue. Use when changes are ready to ship.
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Architecture guide using Next.js App Router's Parallel Routes for Widget-Slot pattern. Separates static layouts from dynamic widgets to achieve separation of concerns, fault isolation, and plug-and-play development.
Run local CI checks and ship changes — create branch, commit, push, and PR. Optionally link to a GitHub issue. Use `--full` to run all workspace checks. Use when changes are ready to ship.
Use when creating new specialist agent definitions for codingbuddy. Covers JSON schema design, expertise definition, system prompt authoring, and differentiation from existing agents.
Use when building or extending MCP (Model Context Protocol) servers. Covers NestJS-based server design, Tools/Resources/Prompts capability design, transport implementation (stdio/SSE), and testing strategies.
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Analyze recent session context archives to identify coding patterns, agent usage, TDD cycle stats, and common EVAL issues. Generates a summary report with data-driven improvement suggestions.
Guided onboarding for new projects - scans tech stack, generates codingbuddy.config.json, sets up adapters, and installs .ai-rules with interactive Q&A.
Decompose specs or implementation plans into independent GitHub issues with dependency graphs, wave grouping, and file overlap analysis for safe parallel execution.
Use when you have a spec or requirements for a multi-step task, before touching code
Use when rendering a multi-agent discussion as a TUI panel. Defines terminal panel layout, component architecture, real-time streaming behavior, and integration points for displaying AgentOpinion data with bordered boxes, severity badges, and consensus indicators.
Use when managing AI session costs, setting budget limits, or preventing cost overruns in autonomous workflows like taskMaestro, autopilot, ralph loops, and parallel agent execution. Defines cost tracking protocol, threshold alerts, and auto-pause mechanism.
Use before shipping, creating PRs, or merging to enforce minimum test coverage thresholds. Covers line, branch, and function coverage. Supports vitest, jest, c8, and istanbul. Blocks shipping when coverage falls below configurable thresholds (default 80%).
Use when a bug or feature request belongs in an upstream, parent, or dependency repository rather than the current one. Guides detection, mapping, and safe cross-repo issue creation with user confirmation.
Use when simple grep/glob is insufficient and you need comprehensive, multi-pass codebase understanding
Use when rendering multi-agent debate, discussion, or review output in the terminal. Formats agent opinions with severity badges, colored identifiers, evidence blocks, and consensus indicators using box drawing characters.
Use when creating implementation plans that need quality review before execution — 4-phase workflow combining plan creation with automated plan-reviewer validation
Background knowledge for tmux session, window, and pane lifecycle management, layout control, inter-pane communication, styling, and troubleshooting. Used by taskMaestro and parallel execution workflows.
Use when build fails, TypeScript errors appear, or compilation breaks. Minimal diff fixes only — no refactoring, no architecture changes.
Use when creating isolated workspaces for parallel execution, feature exploration, or plan implementation. Covers worktree creation, naming conventions, safety checks, and cleanup procedures.
Use when implementation is complete and you need to decide how to integrate the work - merge, PR, or cleanup
Use when receiving PR review feedback or code review comments. Enforces verification-first response to review feedback with anti-sycophancy classification and constructive disagreement protocol.
Use when performing git operations - commits, rebasing, cherry-picking, history cleanup, or conflict resolution. Ensures atomic commits, clean history, and consistent commit message style.
Use when preparing code for review before submitting PRs — covers pre-flight validation, change summary generation, test evidence collection, review focus areas, and structured review request formatting
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims
Convert a PLAN into GitHub issues with native sub-issue hierarchy. Use when a plan is ready to be registered as deployable, independent work items. Creates self-contained issues where each sub-issue can be independently branched, PRed, and merged.
Unified commit and PR workflow. Auto-commits changes, creates/updates PRs with smart issue linking and multi-language support.
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Use after completing parallel/batch work, multi-step plan execution, or any session where surprises occurred (good or bad) and learnings should be captured before context fades.
Use when designing REST or GraphQL APIs - covers OpenAPI spec, resource design, versioning, and documentation
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
Use when writing AI coding rules for codingbuddy that must work consistently across multiple AI tools (Cursor, Claude Code, Codex, GitHub Copilot, Amazon Q, Kiro). Covers rule clarity, trigger design, and multi-tool compatibility.
Use when explaining complex code to new team members, conducting code reviews, onboarding, or understanding unfamiliar codebases. Provides structured analysis from high-level overview to implementation details.
Use when encountering error messages, stack traces, or unexpected application behavior. Provides structured analysis to understand root cause before attempting any fix.
Use when modernizing legacy code or migrating outdated patterns to current best practices. Covers assessment, strangler fig pattern, incremental migration, and risk management.
Use when optimizing code performance, addressing slowness complaints, or measuring application speed improvements